Time series wind power forecasting based on variant Gaussian process and TLBO

Due to the variability and stochastic nature of wind power system, accurate wind power forecasting has an important role in developing reliable and economic power system operation and control strategies. As wind variability is stochastic, Gaussian Process regression has recently been introduced to capture the randomness of wind energy. However, the disadvantages of Gaussian Process regression include its computation complexity and incapability to adapt to time varying time-series systems. A variant Gaussian Process for time series forecasting is introduced in this study to address these issues. This new method is shown to be capable of reducing computational complexity and increasing prediction accuracy. It is further proved that the forecasting result converges as the number of available data approaches innite. Further, a teaching learning based optimization (TLBO) method is used to train the model and to accelerate
the learning rate. The proposed modelling and optimization method is applied to forecast both the wind power generation of Ireland and that from a single wind farm to show the eectiveness of the proposed method.

Improved Real-time State-of-Charge Estimation of LiFePO4 Battery Based on a Novel Thermoelectric Model

Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-ofcharge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is firstly built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviours are captured, thus offering a comprehensive description of the battery thermal and electrical behaviour. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a meta-heuristic algorithm and the least square approach. Further, timevarying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.

Modeling, Analysis and Performance Comparison of Two Direct Sampling DCSK Receivers under Frequency Nonselective Fading Channels

Two direct sampling correlator-type receivers for differential chaos shift keying (DCSK) communication systems under frequency non-selective fading channels are proposed. These receivers operate based on the same hardware platform with different architectures. In the first scheme, namely sum-delay-sum (SDS) receiver, the sum of all samples in a chip period is correlated with its delayed version. The correlation value obtained in each bit period is then compared with a fixed threshold to decide the binary value of recovered bit at the output. On the other hand, the second scheme, namely delay-sum-sum (DSS) receiver, calculates the correlation value of all samples with its delayed version in a chip period. The sum of correlation values in each bit period is then compared with the threshold to recover the data. The conventional DCSK transmitter, frequency non-selective Rayleigh fading channel, and two proposed receivers are mathematically modelled in discrete-time domain. The authors evaluated the bit error rate performance of the receivers by means of both theoretical analysis and numerical simulation. The performance comparison shows that the two proposed receivers can perform well under the studied channel, where the performances get better when the number of paths increases and the DSS receiver outperforms the SDS one.

Searching for swept-up hydrogen and helium in the late-time spectra of 11 nearby Type Ia supernovae

The direct detection of a stellar system that explodes as a Type Ia supernova (SN Ia) has not yet been successful. Various indirect methods have been used to investigate SN Ia progenitor systems but none have produced conclusive results. A prediction of single-degenerate models is that H- (or He-) rich material from the envelope of the companion star should be swept up by the SN ejecta in the explosion. Seven SNe Ia have been analysed to date looking for signs of H-rich material in their late-time spectra and none were detected. We present results from new late-time spectra of 11 SNe Ia obtained at the Very Large Telescope using XShooter and FORS2. We present the tentative detection of Hα emission for SN 2013ct, corresponding to ∼0.007 M_⊙ of stripped/ablated companion star material (under the assumptions of the spectral modelling). This mass is significantly lower than expected for single-degenerate scenarios, suggesting that >0.1 M_⊙ of H-rich is present but not observed. We do not detect Hα emission in the other 10 SNe Ia. This brings the total sample of normal SNe Ia with non-detections (<0.001–0.058 M_⊙) of H-rich material to 17 events. The simplest explanation for these non-detections is that these objects did not result from the explosion of a CO white dwarf accreting matter from a H-rich companion star via Roche lobe overflow or symbiotic channels. However, further spectral modelling is needed to confirm this. We also find no evidence of He-emission features, but models with He-rich companion stars are not available to place mass limits.

Real-time PCR demonstrates high prevalence of Schistosoma japonicum in the Philippines:implications for surveillance and control

BACKGROUND: The Philippines has a population of approximately 103 million people, of which 6.7 million live in schistosomiasis-endemic areas with 1.8 million people being at risk of infection with Schistosoma japonicum. Although the country-wide prevalence of schistosomiasis japonica in the Philippines is relatively low, the prevalence of schistosomiasis can be high, approaching 65% in some endemic areas. Of the currently available microscopy-based diagnostic techniques for detecting schistosome infections in the Philippines and elsewhere, most exhibit varying diagnostic performances, with the Kato-Katz (KK) method having particularly poor sensitivity for detecting low intensity infections. This suggests that the actual prevalence of schistosomiasis japonica may be much higher than previous reports have indicated.

METHODOLOGY/PRINCIPAL FINDINGS: Six barangay (villages) were selected to determine the prevalence of S. japonicum in humans in the municipality of Palapag, Northern Samar. Fecal samples were collected from 560 humans and examined by the KK method and a validated real-time PCR (qPCR) assay. A high S. japonicum prevalence (90.2%) was revealed using qPCR whereas the KK method indicated a lower prevalence (22.9%). The geometric mean eggs per gram (GMEPG) determined by the qPCR was 36.5 and 11.5 by the KK. These results, particularly those obtained by the qPCR, indicate that the prevalence of schistosomiasis in this region of the Philippines is much higher than historically reported.

CONCLUSIONS/SIGNIFICANCE: Despite being more expensive, qPCR can complement the KK procedure, particularly for surveillance and monitoring of areas where extensive schistosomiasis control has led to low prevalence and intensity infections and where schistosomiasis elimination is on the horizon, as for example in southern China.

Secrecy Performance of Wirelessly Powered Wiretap Channels

This paper considers a wirelessly powered wiretap channel, where an energy constrained multi-antenna information source, powered by a dedicated power beacon, communicates with a legitimate user in the presence of a passive eavesdropper. Based on a simple time-switching protocol where power transfer and information transmission are separated in time, we investigate two popular multi-antenna transmission schemes at the information source, namely maximum ratio transmission (MRT) and transmit antenna selection (TAS). Closed-form expressions are derived for the achievable secrecy outage probability and average secrecy rate for both schemes. In addition, simple approximations are obtained at the high signal-to-noise ratio (SNR) regime. Our results demonstrate that by exploiting the full knowledge of channel state information (CSI), we can achieve a better secrecy performance, e.g., with full CSI of the main channel, the system can achieve substantial secrecy diversity gain. On the other hand, without the CSI of the main channel, no diversity gain can be attained. Moreover, we show that the additional level of randomness induced by wireless power transfer does not affect the secrecy performance in the high SNR regime. Finally, our theoretical claims are validated by the numerical results.